Decision list explained

Decision lists are a representation for Boolean functions which can be easily learnable from examples.[1] Single term decision lists are more expressive than disjunctions and conjunctions; however, 1-term decision lists are less expressive than the general disjunctive normal form and the conjunctive normal form.

The language specified by a k-length decision list includes as a subset the language specified by a k-depth decision tree.

Learning decision lists can be used for attribute efficient learning.[2]

Definition

A decision list (DL) of length is of the form:

if then output else if then output ... else if then output

where is the th formula and is the th boolean for

i\in\{1...r\}

. The last if-then-else is the default case, which means formula is always equal to true. A -DL is a decision list where all of formulas have at most terms. Sometimes "decision list" is used to refer to a 1-DL, where all of the formulas are either a variable or its negation.

See also

References

  1. Ronald L. Rivest. Ronald L. Rivest. Learning decision lists. Machine Learning. 2. 3. 229–246. Nov 1987. 10.1023/A:1022607331053. free.
  2. Adam R. Klivans and Rocco A. Servedio, "Toward Attribute Efficient Learning of Decision Lists and Parities", Journal of Machine Learning Research 7:12:587-602 ACM Digital Library full text